The old days
Before the 90s, companies relied on post mail and landline phones, and personal computers were not that democratized in the offices.
Getting business was getting done with pen, paper, and phone.
It was neat, effective. You would not spend hours calculating complicated indicators.
If you wanted a piece of non-trivial information, a deeper insight about your company’s performance, you had to really need it.
And since business was already complicated as it was, you were not going to waste days analysing in depth what had already happened.
Around 2010, iPhone had been invented, the mobile phone industry was turned upside down. It took the mobility to a new level.
Mobile careers made significant improvement in internet speed for mobile, quickly moving from Edge to 3G, 3G+, 4G, and soon 5G. In a matter of a decade.
Information became omnipresent. Now, wherever where you are, in a matter of seconds, you can access millions and millions of data points about anything.
The past in the present
Some of workers that started in the 90s, are now in a management position in the companies we work at.
They started working with pen, paper, and phone. Their brain is wired to see the performance indicators calculated on a napkin.
They don’t necessarily think about which really specific, narrow indicator they can get with the use of data analysis and computer, in order to make a better decision in a certain field.
They have learnt that you don’t need thousands of data point to make decisions. Business have been run until now, and successfully.
Good or bad?
Should we fire all the top level managers who started working in the 90s because they don’t think about very specific indicators we can get from an analysis, and the lack of opportunity we can get from it?
Should we restrict ourselves from diving into the data and keep shallow / top level key indicators?
The good thing about our access to the massive amount data, is that we can learn things in great depth, better understand our performance, our customers.
Our customers don’t want to be bothered about things which do not concern them. We need to analyse large chunks of data and make decisions based on detailed information, on a large number of parameters. We need to tailor a message that is unique to them.
How do Formula 1 teams improve their cars? With telemetry during races. They have done for years things which we now have ubiquitous access : data and computing power. Do we need the level of details of the telemetry for our business performance measurement?
Now, when you open the hood and start digging into the incredible amount of data, two things can happen :
- You get lost in a maze of information, and spend hours bringing up irrelevant data, which has no use for your business. This is highly ineffective,
- You get lost in a maze of information, and create a dashboard with dozens of relevant indicators. It’s amazing, but now you don’t know what to do with it. It brings more confusion than ever before. Everyone focuses on a different one, and you don’t have unity within your business.
Now, I believe that if we can combine the old fashion way of doing it with the new opportunities brought by the access to data, we will get access to a new level of understanding of our business. Our customer, will be the ones benefiting from it.
And if you don’t go this road, your competitor will, and data will be a competitive edge.
Now, what we need to bring from the old days, is the question : what do I actually need. Will this indicator actually help me move my business forward? Or is that a distraction?
If you end up with dozens of indicators, it is important to narrow down : which indicator, or couple / triple of indicators, will make all my other indicators unnecessary, if I remove them?
By diving into data, you get new opportunities of finding relevant indicators. By converging, you actually get the benefit of the old days.
If you can’t measure it, you can’t improve itPeter Drucker
Knowing that the information in your company is most likely structured with a mindset from the old days, the question is now : do you have the data infrastructure to sort, organize data from your different tools, and get insight from it?
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